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Research Article

Mechanistic modeling of copper corrosions in data center environments

Rui Zhang1,2( )Jianshun Zhang1,3Roger Schmidt1Jeremy L. Gilbert4
Department of Mechanical and Aerospace Engineering, College of Engineering and Computer Science, Syracuse University, Syracuse, NY 13244, USA
Buildings and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
SyracuseCoE – New York Center of Excellence in Environmental and Energy Systems, Syracuse University, 727 E. Washington Street, Syracuse, NY 13244, USA
Department of Bioengineering, Clemson University, Clemson – Medical University of South Carolina Bioengineering Program, Charleston, SC 29425, USA
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Abstract

Air-side economizers are increasingly used to take advantage of “free-cooling” in data centers with the intent of reducing the carbon footprint of buildings. However, they can introduce outdoor pollutants to indoor environment of data centers and cause corrosion damage to the information technology equipment. To evaluate the reliability of information technology equipment under various thermal and air-pollution conditions, a mechanistic model based on multi-ion transport and chemical reactions was developed. The model was used to predict Cu corrosion caused by Cl2-containing pollutant mixtures. It also accounted for the effects of temperature (25 ℃ and 28 ℃), relative humidity (50%, 75%, and 95%), and synergism. It also identified higher air temperature as a corrosion barrier and higher relative humidity as a corrosion accelerator, which agreed well with the experimental results. The average root mean square error of the prediction was 13.7 Å. The model can be used to evaluate the thermal guideline for data centers design and operation when Cl2 is present based on pre-established acceptable risk of corrosion in data centers’ environment.

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Building Simulation
Pages 483-492
Cite this article:
Zhang R, Zhang J, Schmidt R, et al. Mechanistic modeling of copper corrosions in data center environments. Building Simulation, 2024, 17(3): 483-492. https://doi.org/10.1007/s12273-023-1088-z

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Received: 14 July 2023
Revised: 02 October 2023
Accepted: 16 October 2023
Published: 27 December 2023
© UT Battelle, LLC 2023
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